Appl Clin Inform 2014; 05(03): 685-698
DOI: 10.4338/ACI-2014-04-RA-0029
Research Article
Schattauer GmbH

Computerized Provider Order Entry Reduces Length of Stay in a Community Hospital

R. Schreiber
1   Holy Spirit Hospital, Camp Hill, PA
,
K. Peters
1   Holy Spirit Hospital, Camp Hill, PA
3   Vibra Healthcare, Mechanicsburg, PA
,
S.H. Shaha
2   Center for Public Policy & Admin, Salt Lake City, UT
4   Allscripts, Chicago, IL
› Institutsangaben
Weitere Informationen

Publikationsverlauf

received: 09. April 2014

accepted: 17. Juni 2014

Publikationsdatum:
19. Dezember 2017 (online)

Summary

Objective: Does computerized provider order entry (CPOE) improve clinical, cost, and efficiency outcomes as quantified in shortened hospital length of stay (LOS)? Most prior studies were done in university settings with home-grown electronic records, and are now 20 years old. This study asked whether CPOE exerts a downward force on LOS in the current era of HITECH incentives, using a vendor product in a community hospital.

Methods: The methodology retrospectively evaluated correlation between CPOE and LOS on a per-patient, per-visit basis over 22 consecutive quarters, organized by discipline. All orders from all areas were eligible, except verbals, and medication orders in the emergency department which were not available via CPOE. These results were compared with quarterly case mix indices organized by discipline. Correlational and regression analyses were cross-checked to ensure validity of R-square coefficients, and data were smoothed for ease of display. Standard models were used to calculate the inflection point.

Results: Gains in CPOE adoption occurred iteratively house-wide, and in each discipline. LOS decreased in a sigmoid shaped curve. The inflection point shows that once CPOE adoption approaches 60%, further lowering of LOS accelerates. Overall there was a 20.2% reduction in LOS correlated with adoption of CPOE. Case mix index increased during the study period showing that reductions in LOS occurred despite increased patient complexity and resource utilization.

Conclusions: There was a 20.2% reduction in LOS correlated with rising adoption of CPOE. CPOE contributes to improved clinical, cost, and efficiency outcomes as quantified in reduced LOS, over and above other processes introduced to lower LOS. CPOE enabled a reduction in LOS despite an increase in the case mix index during the time frame of this study.

Citation: Schreiber R, Peters K, Shaha SH. Computerized provider order entry reduces length of stay in a community hospital. Appl Clin Inf 2014; 5: 685–698

http://dx.doi.org/10.4338/ACI-2014-04-RA-0029

 
  • References

  • 1 Quinn K. After the revolution: DRGs at age 30. Ann Intern Med 2014; 160 (Suppl. 06) 426-429.
  • 2 Weeks WB, Rauh SS, Wadsworth EB, Weinstein JN. The unintended consequences of bundled payments. Ann Intern Med 2013; 158 (01) 62-64.
  • 3 Chen C, Ackerly DC. Beyond ACOs and bundled payments: Medicare’s shift toward accountability in feefor-service. JAMA 2014; 311 (07) 673-674.
  • 4 Wright A, Ash JS, Erickson JL, Wasserman J, Bunce A, Stanescu A, St Hilaire D, Panzenhagen M, Gebhardt E, McMullen C, Middleton B, Sittig DF. A qualitative study of the activities performed by people involved in clinical decision support: recommended practices for success. J Am Med Inform Assoc 2014; 21 (03) 464-472.
  • 5 Ash JS, Sittig DF, Guappone KP, Dykstra RH, Richardson J, Wright A, Carpenter J, McMullen C, Shapiro M, Bunce A, Middleton B. Recommended practices for computerized clinical decision support and knowledge management in community settings: a qualitative study. BMC Med Inform Decis Mak 2012; 12: 6-25.
  • 6 111th Congress of the United States of America. H. R 1. The American Recovery and Reinvestment Act of 2009, Title XIII found at: http://www.healthit.gov/sites/default/files/hitech_act_ex cerpt_from_arra_with_index.pdf (accessed 2 June 2014).
  • 7 Tierney WM, Miller ME, Overhage JM, McDonald CJ. Physician inpatient order writing on microcomputer workstations. Effects on resource utilization. JAMA 1993; 269 (03) 379-383.
  • 8 Evans RS, Pestotnik SL, Classen DC, Clemmer TP, Weaver LK, Orme Jr JF, Lloyd JF, Burke JP. A computer-assisted management program for antibiotics and other antiinfective agents. N Engl J Med 1998; 338 (04) 232-238.
  • 9 Mekhjian HS, Kumar RR, Kuehn L, Bentley TD, Teater P, Thomas A, Payne B, Ahmad A. Immediate benefits realized following implementation of physician order entry at an academic medical center. J Am Med Inform Assoc 2002; 9 (05) 529-539.
  • 10 Hwang JI, Park HA, Bakken S. Impact of a physician’s order entry (POE) system on physicians’ ordering patterns and patient length of stay. Int J Med Inform 2002; 65 (03) 213-223.
  • 11 Kuperman GJ, Gibson RF. Computer Physician Order Entry: Benefits, Costs, and Issues. Ann Intern Med 2003; 139: 31-39.
  • 12 Spalding SC, Mayer PH, Ginde AA, Lowenstein SR, Yaron M. Impact of computerized physician order entry on ED patient length of stay. Am J Emerg Med 2011; 29 (02) 207-211.
  • 13 Al-Dorzi HM, Tamim HM, Cherfan A, Hassan MA, Taher S, Arabi YM. Impact of computerized physician order entry (CPOE) system on the outcome of critically ill adult patients: a before-after study. BMC Med Inform Decis Mak 2011; 11: 71-79.
  • 14 Carmichael A, Tully M. Key Strategies for Ensuring Clinical Revenue Integrity with ICD-10. American Health Information Management Association (AHIMA); Chicago: 2012
  • 15 Campbell DT, Stanley JC. Experimental and Quasi-Experimental Designs for Research. Boston: Houghton Mifflin Company,; 1963
  • 16 Rogozin BA. A/a013160. In Hazewinkel M. editor. Encyclopedia of Mathematics. New York: Springer; 2001
  • 17 Zeger SL, Liang K-Y, Albert PS. Models for longitudinal data: A generalized estimating equation approach. Biometrics (International Biometric Society) 1998; 44 (04) 1049-1060.
  • 18 McCullagh P, Nelder J. Generalized Linear Models. London: Chapman and Hall.; 1989
  • 19 Linacre JM. Percentages with continuous Rasch models. Rasch Measurement Transactions 2001; 14 (04) 771-774.
  • 20 Hazewinkel M. editor. Point of inflection. Encyclopedia of Mathematics. New York: Springer; 2001
  • 21 Brodsky L, Shaha SH. Integrated outcomes approach to improvement in healthcare. In: Coughlin KM. et al., editors. 2001 Medical Outcomes & Guidelines Sourcebook. New York: Faulkner & Gray; 2000
  • 22 Bates DW, Boyle DL, VanderVliet MB, Schneider J, Leape L. Relationship between medication errors and adverse drug events. J Gen Intern Med 1995; 10 (04) 199-205.
  • 23 Centers for Medicare & Medicaid Services (CMS).. Eligible Hospital and Critical Access Hospital Meaningful Use Core Measures Measure 1 of 16, Stage 2, CPOE for Medication, Laboratory and Radiology Orders. http://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/downloads Stage2_HospitalCore_1_CPOE_MedicationOrders.pdf (accessed 2 June 2014).
  • 24 Eslami S, de Keizer NF, Abu-Hanna A. The impact of computerized physician medication order entry in hospitalized patients –a systematic review. Int J Med Inform 2008; 77 (06) 365-376.
  • 25 Ali NA, Mekhijian HS, Kuehn PL, Bentley TD, Kumar R, Ferketich AK, Hoffman SP. Specificity of computerized physician order entry has a significant effect on the efficiency of workflow for critically ill patients. Crit Care Med 2005; 33 (01) 110-114.
  • 26 Westbrook JI, Georgiou A, Lam M. Does computerised provider order entry reduce test turnaround times? A before-and-after study at four hospitals. Stud Health Technol Inform 2009; 150: 527-531.
  • 27 Rothschild J. Computerized physician order entry in the critical care and general inpatient setting: a narrative review. J Crit Care 2004; 19 (04) 271-278.
  • 28 Ohl CA, Luther VP. Antimicrobial stewardship for inpatient facilities. J Hosp Med 2011; 6 S1 S4-S15.
  • 29 Shea S, Sideli RV, DuMouchel W, Pulver G, Arons RR, Clayton PD. Computer-generated informational messages directed to physicians: effect on length of hospital stay. J Am Med Inform Assoc 1995; 2 (01) 58-64.
  • 30 Vartak S, Crandall DK, Brokel JM, Wakefield DS, Ward MM. Transformation of Emergency Department processes of care with EHR, CPOE, and ER event tracking systems. HIM J 2009; 38 (02) 27-32.